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Application of Decomposition Methods in the Filtering of Event-Related Potentials

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Data Mining for Biomarker Discovery

Part of the book series: Springer Optimization and Its Applications ((SOIA,volume 65))

Abstract

The processes giving rise to an event-related potential engage several evoked and induced oscillatory components, which reflect phase or nonphase locked activity throughout the multiple trials of an experiment. The separation and identification of such components could not only serve diagnostic purposes but also facilitate the design of brain–computer interface systems. However, the effective analysis of components is hindered by many factors including the complexity of the EEG signal and its variation over the trials. In this chapter, we study several measures for the identification of the nature of independent components and propose a complete methodology for efficient decomposition of the rich information content embedded in the multichannel EEG recordings associated with the multiple trials of an event-related experiment. The efficiency of the proposed methodology is demonstrated through simulated and real experiments.

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Acknowledgements

Present work was supported by a research fund from the Research Committee of the Technical University of Crete. The authors would like to thank Prof. Cristin Bigan at the Ecological University of Bucharest, Romania for kindly providing the EEG dataset.

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Authors and Affiliations

  1. Department of Electronic and Computer Engineering, Technical University of Crete, Chania, 73100, Greece

    Kostas Michalopoulos, Vasiliki Iordanidou & Michalis Zervakis

Authors
  1. Kostas Michalopoulos
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  2. Vasiliki Iordanidou
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  3. Michalis Zervakis
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Corresponding author

Correspondence to Kostas Michalopoulos .

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Editors and Affiliations

  1. , Department of Industrial & Systems Engin, University of Florida, Weil Hall 401, Gainesville, 32611-6595, Florida, USA

    Panos M. Pardalos

  2. , Department of Industrial & Systems Engin, University of Florida, Weil Hall 401, Gainesville, 32611, Florida, USA

    Petros Xanthopoulos

  3. Dept. Electronic & Computer, Engineering, Technical University of Crete, Chania, Crete, 731 00, Greece

    Michalis Zervakis

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Michalopoulos, K., Iordanidou, V., Zervakis, M. (2012). Application of Decomposition Methods in the Filtering of Event-Related Potentials. In: Pardalos, P., Xanthopoulos, P., Zervakis, M. (eds) Data Mining for Biomarker Discovery. Springer Optimization and Its Applications(), vol 65. Springer, Boston, MA. https://doi.org/10.1007/978-1-4614-2107-8_2

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